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DOE OSTI2023

The Bimodal Absorption System Imaging Campaign (BASIC). I. A Dual Population of Low-metallicity Absorbers at z < 1

The bimodal absorption system imaging campaign (BASIC) aims to characterize the galaxy environments of a sample of 36 H I-selected partial Lyman limit systems (pLLSs) and Lyman limit systems (LLSs) in 23 QSO fields at z ≲ 1. These pLLSs/LLSs provide a unique sample of absorbers with unbiased and well-constrained metallicities, allowing us to explore the origins of metal-rich and low-metallicity circumgalactic medium (CGM) at z < 1. Here we present Keck/KCWI and Very Large Telescope/MUSE observations of 11 of these QSO fields (19 pLLSs) that we combine with Hubble Space Telescope/Advanced Camera for Surveys imaging to identify and characterize the absorber-associated galaxies at 0.16 ≲ z ≲ 0.84. We find 23 unique absorber-associated galaxies, with an average of one associated galaxy per absorber. For seven absorbers, all with <10% solar metallicities, we find no associated galaxies with logM * ≳ 9.0 within ρ/R vir and |Δv|/v esc ≤ 1.5 with respect to the absorber. We do not find any strong correlations between the metallicities or H I column densities of the gas and most of the galaxy properties, except for the stellar mass of the galaxies: the low-metallicity ([X/H] ≤ –1.4) systems have a probability of $0.39_{–0.15}^{+0.16}$ for having a host galaxy with logM * ≥ 9.0 within ρ/R vir ≤ 1.5, while the higher metallicity absorbers have a probability of $0.78_{–0.13}^{+0.10}$. This implies metal-enriched pLLSs/LLSs at z < 1 are typically associated with the CGM of galaxies with logM * > 9.0, whereas low-metallicity pLLSs/LLSs are found in more diverse locations, with one population arising in the CGM of galaxies and another more broadly distributed in overdense regions of the universe. Using absorbers not associated with galaxies, we estimate the unweighted geometric mean metallicity of the intergalactic medium to be [X/H] ≲ –2.1 at z < 1, which is lower than previously estimated.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Investigation of the $\gamma $-ray Properties of the $2^+$ States in $^{14}$C

The properties of the 2$^+_1$ and 2$^+_2$ excited states in 14 C were studied in an experiment conducted at Argonne National Laboratory. A 9 Be( 6 Li,pγ) fusion-evaporation reaction and the GRETINA-ORRUBA setup were employed to populate states of 14 C and detect γ-particle coincidence events. Finally, the precise determination of the 2$^+_1$ level energy, complemented by the estimation of the γ-ray branch of the 2$^+_2$ near-threshold state, will serve as a benchmark to test the Shell Model Embedded in the Continuum calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1982

Deposition and dose from the 18 May 1980 eruption of Mount St. Helens

The downwind deposition and radiation doses was calculated for the tropospheric part of the ash cloud from the May 18, 1980 eruption of Mount St. Helens, by using a large cloud diffusion model. The naturally occurring radionnuclides of radium and thorium, whose radon daughters normally seep very slowly from the rocks and soil, were violently released to the atmosphere. The largest dose to an individual from these nuclides is small, but the population dose to those affected by the radioactivity in the ash is about 100 person rem. This population dose from Mount St. Helens is much greater than the annual person rem routinely released by a typical large nuclear power plant. It is estimated that subsequent eruptions of Mount St. Helens have doubled or tripled the person rem calculated from the initial large eruption. The long range global ash deposition of the May 18 eruption is estimated through 1984, by use of a global deposition model. The maximum deposition is nearly 1000 kg square km and occurs in the spring of 1981 over middle latitudes of the Northern Hemisphere.

Peterson, K. R.↗

NASA NTRS1992

Constraints on the age and evolution of the Galaxy from the white dwarf luminosity function

The white dwarf disk luminosity function is explored using observational results of Liebert et al. (1988, 1989) as a template for comparison, and the cooling curves of Wood (1990, 1991) as the input basis functions for the integration. The star formation rate over the history of the Galaxy is found to be constant to within an order of magnitude, and the disk age lies in the range 6-13.5 Gyr, where roughly 40 percent of the uncertainty is due to the observational uncertainties. Using the best current estimates as inputs to the integration, the disk ages range from 7.5 to 11 Gyr, i.e., they are substantially younger than most estimates for the halo globular clusters but in reasonable agreement with those for the disk globular clusters and open clusters. The ages of these differing populations, taken together, are consistent with the pressure-supported collapse models of early spiral Galactic evolution.

Wood, M. A.↗

NASA NTRS1995

Ulysses magnetic field observations of fluctuations within polar coronal flows

The Ulysses spacecraft has gathered data from within flows from the Sun's southern polar coronal hole, the first in situ measurement of this region. We present a brief analysis of the heliospheric magnetic field data from this region, using a fractal method. As is the case near the ecliptic, estimated spectral exponents are near 5/3 on spacecraft scales of seconds to minutes. On longer time scales, however, there appears to be a significantly different population in polar flows, which is similar to that found by the Helios spacecraft in fast solar wind flows at 0.3 AU.

Horbury, T.↗

NASA NTRS2014

Aggregation Tool to Create Curated Data albums to Support Disaster Recovery and Response

Despite advances in science and technology of prediction and simulation of natural hazards, losses incurred due to natural disasters keep growing every year. Natural disasters cause more economic losses as compared to anthropogenic disasters. Economic losses due to natural hazards are estimated to be around $6-$10 billion dollars annually for the U.S. and this number keeps increasing every year. This increase has been attributed to population growth and migration to more hazard prone locations such as coasts. As this trend continues, in concert with shifts in weather patterns caused by climate change, it is anticipated that losses associated with natural disasters will keep growing substantially. One of challenges disaster response and recovery analysts face is to quickly find, access and utilize a vast variety of relevant geospatial data collected by different federal agencies such as DoD, NASA, NOAA, EPA, USGS etc. Some examples of these data sets include high spatio-temporal resolution multi/hyperspectral satellite imagery, model prediction outputs from weather models, latest radar scans, measurements from an array of sensor networks such as Integrated Ocean Observing System etc. More often analysts may be familiar with limited, but specific datasets and are often unaware of or unfamiliar with a large quantity of other useful resources. Finding airborne or satellite data useful to a natural disaster event often requires a time consuming search through web pages and data archives. Additional information related to damages, deaths, and injuries requires extensive online searches for news reports and official report summaries. An analyst must also sift through vast amounts of potentially useful digital information captured by the general public such as geo-tagged photos, videos and real time damage updates within twitter feeds. Collecting and aggregating these information fragments can provide useful information in assessing damage in real time and help direct recovery efforts. The search process for the analyst could be made much more efficient and productive if a tool could go beyond a typical search engine and provide not just links to web sites but actual links to specific data relevant to the natural disaster, parse unstructured reports for useful information nuggets, as well as gather other related reports, summaries, news stories, and images. This presentation will describe a semantic aggregation tool developed to address similar problem for Earth Science researchers. This tool provides automated curation, and creates "Data Albums" to support case studies. The generated "Data Albums" are compiled collections of information related to a specific science topic or event, containing links to relevant data files (granules) from different instruments; tools and services for visualization and analysis; information about the event contained in news reports, and images or videos to supplement research analysis. An ontology-based relevancy-ranking algorithm drives the curation of relevant data sets for a given event. This tool is now being used to generate a catalog of Hurricane Case Studies at Global Hydrology Resource Center (GHRC), one of NASA's Distribute Active Archive Centers. Another instance of the Data Albums tool is currently being created in collaboration with NASA/MSFC's SPoRT Center, which conducts research on unique NASA products and capabilities that can be transitioned to the operational community to solve forecast problems. This new instance focuses on severe weather to support SPoRT researchers in their model evaluation studies

Ramachandran, Rahul↗

NASA NTRS2016

Large Gain in Air Quality Compared to an Alternative Anthropogenic Emissions Scenario

During the last 30 years, significant effort has been made to improve air quality through legislation for emissions reduction. Global three-dimensional chemistrytransport simulations of atmospheric composition over the past 3 decades have been performed to estimate what the air quality levels would have been under a scenario of stagnation of anthropogenic emissions per capita as in 1980, accounting for the population increase (BA1980) or using the standard practice of neglecting it (AE1980), and how they compare to the historical changes in air quality levels. The simulations are based on assimilated meteorology to account for the yearto- year observed climate variability and on different scenarios of anthropogenic emissions of pollutants. The ACCMIP historical emissions dataset is used as the starting point. Our sensitivity simulations provide clear indications that air quality legislation and technology developments have limited the rapid increase of air pollutants. The achieved reductions in concentrations of nitrogen oxides, carbon monoxide, black carbon, and sulfate aerosols are found to be significant when comparing to both BA1980 and AE1980 simulations that neglect any measures applied for the protection of the environment. We also show the potentially large tropospheric air quality benefit from the development of cleaner technology used by the growing global population. These 30-year hindcast sensitivity simulations demonstrate that the actual benefit in air quality due to air pollution legislation and technological advances is higher than the gain calculated by a simple comparison against a constant anthropogenic emissions simulation, as is usually done. Our results also indicate that over China and India the beneficial technological advances for the air quality may have been masked by the explosive increase in local population and the disproportional increase in energy demand partially due to the globalization of the economy.

Law (Jurisprudence)↗

NASA NTRS2006

Improving the Near-Earth Micrometeoroid and Orbital Debris Environment Definition with LADC

The Large Area Debris Collector (LADC) is a 10 m(sup 2) aerogel and acoustic sensor system designed to characterize and collect submillimeter micrometeoroids and orbital debris on the International Space Station (ISS). The project is led by the U.S. Naval Research Laboratory (NRL) with major collaboration by the NASA Orbital Debris Program Office at Johnson Space Center. The U.S. Department of Defense Space Test Program (STP) is responsible for the integration, deployment, and retrieval of the system. The deployment is scheduled for August 2007 with an orbital collection period of one to two years. The combined area time product of LADC will provide a much needed orbital debris population update in the size regime that is important to the safety community - 100 mm and larger. Another key element for LADC is the source identification of the collected samples. Impact features such as track length and track volume can be used to estimate the impact speed and direction of any selected residual embedded in aerogel. Acoustic sensors can provide impact timing and impact location information. The combined dynamical signatures make it possible to reconstruct the orbits of some of the collected samples and lead to their source identification. Compositional analysis on the residuals can also separate debris from meteoroids and provide additional population breakdown for orbital debris (e.g., Al, paint, steel, Al2O3). To maximize the science return and minimize potential contamination from other ISS modules, a careful selection of the location and orientation of LADC on the ISS is needed. Key issues and engineering constraints encountered during mission preparation, and the expected science return based on the mission configuration, are summarized in this paper.

Liou, J.-C.↗

DOE OSTI2026

Chasing Gamma-Ray Signals from Binary Neutron Star Coalescences with the Cherenkov Telescope Array: Prospects and Observing Strategies

The detection of gravitational waves (GWs) from a binary neutron star (BNS) merger by Advanced LIGO and Advanced Virgo (GW170817), together with its electromagnetic counterpart, the short gamma-ray burst GRB 170817A, heralded the birth of multimessenger astronomy. The detection of TeV emission from GRBs motivates follow-up observations with the Cherenkov Telescope Array Observatory (CTAO), which is ideal for detecting such signals due to its unprecedented sensitivity, rapid response, and wide-field survey capabilities. The aim of this work is to evaluate GeV–TeV GW follow-up strategies for CTAO using a multistep simulation pipeline and to estimate the expected rate of joint GW–GRB detections during observing run O5. Using a simulated sample of BNS systems with corresponding GW detections, gamma-ray emission is simulated through phenomenological prescriptions based on the observed population of short GRBs, including off-axis jet scenarios. CTAO observations are simulated to account for instrument response, sky tiling strategies, integration times, and varying observing conditions. Strategies with variable and constant integration times are investigated. We find that, via an optimized follow-up strategy, about 5% of simulated GW-associated short GRBs produce GeV–TeV radiation detectable by CTAO. Detectability is strongly influenced by the jet opening angle and viewing angle, suggesting that even rough estimates of the viewing angle in GW alerts could enhance targeting. This framework motivates future follow-ups of GW-detectable events, including neutron star–black hole mergers, and further supports the development of advanced strategies incorporating galaxy distributions and synergies with future detectors such as the Einstein Telescope.

Abe, S. [University of Tokyo] (ORCID:0000000172503↗

DOE OSTI2021

Dark Energy Survey Year 3 results: galaxy sample for BAO measurement

Here, we present and validate the galaxy sample used for the analysis of the baryon acoustic oscillation (BAO) signal in the Dark Energy Survey (DES) Y3 data. The definition is based on a colour and redshift-dependent magnitude cut optimized to select galaxies at redshifts higher than 0.5, while ensuring a high-quality determination. The sample covers ~ 4100 square degrees to a depth of i = 22.3 (AB) at 10σ. It contains 7,031,993 galaxies in the redshift range from z = 0.6 to 1.1, with a mean effective redshift of 0.835. Redshifts are estimated with the machine learning algorithm DNF, and are validated using the VIPERS PDR2 sample. We find a mean redshift bias of z bias ~ 0.01 and a mean uncertainty, in units of 1 + z, of σ 68 ~ 0.03$. We evaluate the galaxy population of the sample, showing it is mostly built upon Elliptical to Sbc types. Furthermore, we find a low level of stellar contamination of ≲ 4 %. We present the method used to mitigate the effect of spurious clustering coming from observing conditions and other large-scale systematics. We apply it to the BAO sample and calculate weights that are used to get a robust estimate of the galaxy clustering signal. This paper is one of a series dedicated to the analysis of the BAO signal in DES Y3. In the companion papers, we present the galaxy mock catalogues used to calibrate the analysis and the angular diameter distance constraints obtained through the fitting to the BAO scale.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2020

In-Time UAV Flight-Trajectory Estimation and Tracking Using Bayesian Filters

Rapid increase of UAV operation in the next decade in areas of on-demand delivery, medical transportation services, law enforcement, traffic surveillance and several others pose potential risks to the low altitude airspace above densely populated areas. Safety assessment of airspace demands the need for a novel UAV traffic management (UTM) framework for regulation and tracking of the vehicles. Particularly for low-altitude UAV operations, quality of GPS measurements feeding into the UAV is often compromised by loss of communication link caused by presence of trees or tall buildings in proximity to the UAV flight path. Inaccurate GPS locations may yield to unreliable monitoring and inaccurate prognosis of remaining battery life and other safety metrics which rely on future expected trajectory of the UAV. This work therefore proposes a generalized monitoring and prediction methodology for autonomous UAVs using in-time GPS measurements. Firstly, a typical 4D smooth trajectory generation technique from a series of waypoint locations with associated expected times-of-arrival based on B-spline curves is presented. Initial uncertainty in the vehicle's expected cruise velocity is quantified to compute confidence intervals along the entire flight trajectory using error interval propagation approach. Further, the generated planned trajectory is considered as the prior knowledge which is updated during its flight with incoming GPS measurements in order to estimate its current location and corresponding kinematic profiles. Estimation of position is denoted in dicrete state-space representation such that position at a future time step is derived from position and velocity at current time step and expected velocity at the future time step. A linear Bayesian filtering algorithm is employed to efficiently refine position estimation from noisy GPS measurements and update the confidence intervals. Further, a dynamic re-planning strategy is implemented to incorporate unexpected detour or delay scenarios. Finally, critical challenges related to uncertainty quantification in trajectory prognosis for autonomous vehicles are identified, and potential solutions are discussed at the end of the paper. The entire monitoring framework is demonstrated on real UAV flight experiments conducted at the NASA Langley Research Center.

Banerjee, Portia↗

DOE OSTI2023

Rapid screening of secondary aromatic metabolites in Populus trichocarpa leaves

Abstract Background High-throughput metabolomics analytical methodology is needed for population-scale studies of bioenergy-relevant feedstocks such as poplar ( Populus sp.). Here, the authors report the relative abundance of extractable aromatic metabolites in Populus trichocarpa leaves rapidly estimated using pyrolysis-molecular beam mass spectrometry (py-MBMS). Poplar leaves were analyzed in conjunction with and validated by GC/MS analysis of extracts to determine key spectral features used to build PLS models to predict the relative composition of extractable aromatic metabolites in whole poplar leaves. Results The Pearson correlation coefficient for the relative abundance of extractable aromatic metabolites based on ranking between GC/MS analysis and py-MBMS analysis of the Boardman leaf set was 0.86 with R 2 = 0.76 using a simplified prediction approach from select ions in MBMS spectra. Metabolites most influential to py-MBMS spectral features in the Clatskanie set included the following compounds: catechol, salicortin, salicyloyl-coumaroyl-glucoside conjugates, α-salicyloylsalicin, tremulacin, as well as other salicylates, trichocarpin, salicylic acid, and various tremuloidin conjugates. Ions in py-MBMS spectra with the highest correlation to the abundance of extractable aromatic metabolites as determined by GC/MS analysis of extracts, included m/z 68, 71, 77, 91, 94, 105, 107, 108, and 122, and were used to develop the simplified prediction approach without PLS models or a priori measurements. Conclusions The simplified py-MBMS method is capable of rapidly screening leaf tissue for relative abundance of extractable aromatic secondary metabolites to enable prioritization of samples in large populations requiring comprehensive metabolomics that will ultimately inform plant systems biology models and advance the development of optimized biomass feedstocks for renewable fuels and chemicals.

09 BIOMASS FUELS↗

NASA NTRS2016

Uncertainty Estimates of Psychoacoustic Thresholds Obtained from Group Tests

Adaptive psychoacoustic test methods, in which the next signal level depends on the response to the previous signal, are the most efficient for determining psychoacoustic thresholds of individual subjects. In many tests conducted in the NASA psychoacoustic labs, the goal is to determine thresholds representative of the general population. To do this economically, non-adaptive testing methods are used in which three or four subjects are tested at the same time with predetermined signal levels. This approach requires us to identify techniques for assessing the uncertainty in resulting group-average psychoacoustic thresholds. In this presentation we examine the Delta Method of frequentist statistics, the Generalized Linear Model (GLM), the Nonparametric Bootstrap, a frequentist method, and Markov Chain Monte Carlo Posterior Estimation and a Bayesian approach. Each technique is exercised on a manufactured, theoretical dataset and then on datasets from two psychoacoustics facilities at NASA. The Delta Method is the simplest to implement and accurate for the cases studied. The GLM is found to be the least robust, and the Bootstrap takes the longest to calculate. The Bayesian Posterior Estimate is the most versatile technique examined because it allows the inclusion of prior information.

Rathsam, Jonathan↗

DOE OSTI2024

Estimated impacts of forest restoration scenarios on smoke exposures among outdoor agricultural workers in California

Abstract As wildfires continue to worsen across western United States, forest managers are increasingly employing prescribed burns as a way to reduce excess fuels and future wildfire risk. While the ecological benefits of these fuel treatments are clear, little is known about the smoke exposure tradeoffs of using prescribed burns to mitigate wildfires, particularly among at-risk populations. Outdoor agricultural workers are a population at increased risk of smoke exposure because of their time spent outside and the physical demands of their work. Here, we assess the smoke exposure impacts among outdoor agricultural workers resulting from the implementation of six forest management scenarios proposed for a landscape in the Central Sierra, California. We leverage emissions estimates from LANDIS-II to model daily PM 2.5 concentrations with the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) and link those to agricultural employment data from the Bureau of Labor Statistics. We find a u-shaped result, in that moderate amounts of prescribed burning result in the greatest reduction in total smoke exposure among outdoor agricultural workers, particularly during months of peak agricultural activity due to wildfire-specific smoke reductions. The reduction in total smoke exposure, relative to scenarios with the least amount of management, decreases as more prescribed burning is applied to the landscape due to the contributions of the fuel treatments themselves to overall smoke burden. The results of this analysis may contribute to preparedness efforts aimed at reducing smoke exposures among outdoor agricultural workers, while also informing forest management planning for this specific landscape.

Environmental Sciences & Ecology↗

DOE OSTI2022

Blanco DECam Bulge Survey (BDBS). VII. Multiple Populations in Globular Clusters of the Galactic Bulge

We present photometric evidence for multiple stellar populations (MPs) in 14 globular clusters (GCs) toward the southern Galactic bulge. The photometric data come as part of the Blanco DECam Bulge Survey, which is a deep, wide-field near-UV-near-IR (ugrizY) survey of the southern Galactic bulge. Here, we present the first systematic study of bulge GC multiple populations with deep photometry including the u band, which is a crucial indicator of the abundance of CNO-bearing molecules in stellar atmospheres. We identify cluster members using Gaia EDR3 proper motion measurements, and then isolate red giant branch stars using r versus u - r color–magnitude diagrams. We find evidence suggesting all 14 clusters host at least two populations, and NGC 6441, NGC 6626, and NGC 6656 appear to have at least three populations. Many of these clusters are not part of the Hubble Space Telescope (HST) surveys nor do they have comprehensive spectroscopic analyses so we are presenting the first evidence of MPs in several clusters. Not only do we find a strong anticorrelation between the fraction of first-generation stars and cluster absolute V magnitude, but the correlation coefficient and cluster-to-cluster scatter are similar to the results obtained from HST. Our ground-based data extend to much larger radial distances than similar HST observations, enabling a reliable estimate of the global fraction of first-generation stars in each cluster. This study demonstrates that ground-based u-band photometry as provided by DECam will prove powerful in the study of multiple populations in resolved GCs.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Impacts of climate change, population growth, and power sector decarbonization on urban building energy use

Climate, technologies, and socio-economic changes will influence future building energy use in cities. However, current low-resolution regional and state-level analyses are insufficient to reliably assist city-level decision-making. Here we estimate mid-century hourly building energy consumption in 277 U.S. urban areas using a bottom-up approach. The projected future climate change results in heterogeneous changes in energy use intensity (EUI) among urban areas, particularly under higher warming scenarios, with on average 10.1–37.7% increases in the frequency of peak building electricity EUI but over 110% increases in some cities. For each 1 °C of warming, the mean city-scale space-conditioning EUI experiences an average increase/decrease of ~14%/ ~ 10% for space cooling/heating. Heterogeneous city-scale building source energy use changes are primarily driven by population and power sector changes, on average ranging from –9% to 40% with consistent south–north gradients under different scenarios. Across the scenarios considered here, the changes in city-scale building source energy use, when averaged over all urban areas, are as follows: –2.5% to –2.0% due to climate change, 7.3% to 52.2% due to population growth, and –17.1% to –8.9% due to power sector decarbonization. Our findings underscore the necessity of considering intercity heterogeneity when developing sustainable and resilient urban energy systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2017

Carotid Intima Media Thickness in the Astronaut Corps: Association to Spacecraft

Background: Carotid Intima Media Thickness (CIMT) has been demonstrated to be predictive of future cardiovascular events. Within various populations, radiation exposure, stress, and physical confinement have all been linked to an increased CIMT. Recent research discovered CIMT was significantly increased in ten long duration astronauts from pre-flight to four days post flight. The relationship between spaceflight and CIMT is not understood and trends in CIMT within the larger astronaut population are unknown. Methods: In 2010, CIMT was offered as part of the astronaut annual exam at the JSC Flight Medicine Clinic using a standardized CIMT screening protocol and professional sonographers. Between 2010 and 2016, CIMT measurements were collected on 213 NASA astronauts and payload specialists. The values used in this retrospective chart review are the mean of the CIMT from the right and left. Spaceflight exposure was categorized based on the total number of days spent in space at the time of the ground-based ultrasound (0, 1-29, 30-100, 101-200, ≥200). Linear regression with generalized estimating equations were used to estimate the association between spaceflight exposures and CIMT. Results: 530 studies were completed among 213 astronauts with a mean of 2.5 studies (range 1-6) per astronaut over the six year period. As in other populations, CIMT was significantly associated with age; however, gender was not. While there was no significant direct correlation between total spaceflight exposure and CIMT found, astronauts with 30-100 spaceflight days and astronauts with greater than 100 spaceflight days had significantly increased CIMT over astronauts who had never flown (p=0.002 and p=<0.0001 respectively) after adjustment for age. Conclusion: Further work is needed to fully understand CIMT and its association to spaceflight. Current occupational surveillance activities are under way to study CIMT values in conjunction with other cardiovascular risk factors among astronauts as compared to the general population.

Suffredini, John↗

DOE OSTI2021

Explaining the trends and variability in the United States tornado records using climate teleconnections and shifts in observational practices

The annual frequency of tornadoes during 1950–2018 across the major tornado-impacted states were examined and modeled using anthropogenic and large-scale climate covariates in a hierarchical Bayesian inference framework. Anthropogenic factors include increases in population density and better detection systems since the mid-1990s. Large-scale climate variables include El Niño Southern Oscillation (ENSO), Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), Arctic Oscillation (AO), and Atlantic Multi-decadal Oscillation (AMO). The model provides a robust way of estimating the response coefficients by considering pooling of information across groups of states that belong to Tornado Alley, Dixie Alley, and Other States, thereby reducing their uncertainty. The influence of the anthropogenic factors and the large-scale climate variables are modeled in a nested framework to unravel secular trend from cyclical variability. Population density explains the long-term trend in Dixie Alley. The step-increase induced due to the installation of the Doppler Radar systems explains the long-term trend in Tornado Alley. NAO and the interplay between NAO and ENSO explained the interannual to multi-decadal variability in Tornado Alley. PDO and AMO are also contributing to this multi-time scale variability. SOI and AO explain the cyclical variability in Dixie Alley. This improved understanding of the variability and trends in tornadoes should be of immense value to public planners, businesses, and insurance-based risk management agencies.

54 ENVIRONMENTAL SCIENCES↗